Walchensee wind: forecast and measurements

30 days of forecast vs. what actually happened at the lake. Click a single day to see its details.

Last 30 days

Rule-based forecast (actually used)
ML-based forecast — logistic (experimental)
ML-based forecast — HistGradientBoosting (black-box model, experimental)
Actual measurements (session ≥ 1 h)
Wed Sep 23 Thu Oct 22
session (≥ 1 h ≥ 11 kt) marginal (≥ 1 h ≥ 8 kt) no wind no data thunderstorm (forecast rows: predicted · actual row: observed)

Oct 14, 2026

81106:0021:0010:09 · avg 10.8 kt · gust 13.0 kt10:10 · avg 11.9 kt · gust 17.3 kt10:55 · avg 8.5 kt · gust 13.0 kt11:29 · avg 1.5 kt · gust 3.2 kt11:39 · avg 3.3 kt · gust 6.5 kt11:49 · avg 3.8 kt · gust 6.5 kt11:59 · avg 1.8 kt · gust 3.2 kt12:09 · avg 0.9 kt · gust 2.2 kt12:19 · avg 0.3 kt · gust 2.2 kt12:29 · avg 1.4 kt · gust 3.2 kt12:39 · avg 0.7 kt · gust 2.2 kt12:49 · avg 0.3 kt · gust 1.6 kt12:59 · avg 0.7 kt · gust 4.9 kt13:09 · avg 3.9 kt · gust 8.6 kt13:19 · avg 7.0 kt · gust 9.2 kt13:29 · avg 5.6 kt · gust 10.8 kt13:39 · avg 5.7 kt · gust 9.2 kt13:49 · avg 6.0 kt · gust 10.3 kt13:59 · avg 5.9 kt · gust 8.6 kt14:09 · avg 5.6 kt · gust 8.6 kt14:19 · avg 5.7 kt · gust 8.6 kt14:29 · avg 4.6 kt · gust 7.6 kt14:39 · avg 4.9 kt · gust 8.6 kt14:49 · avg 5.1 kt · gust 8.6 kt14:59 · avg 4.0 kt · gust 7.6 kt15:09 · avg 4.4 kt · gust 7.6 kt15:19 · avg 1.9 kt · gust 4.3 kt15:29 · avg 2.1 kt · gust 4.3 kt15:39 · avg 1.9 kt · gust 4.3 kt15:49 · avg 1.8 kt · gust 3.2 kt15:59 · avg 0.9 kt · gust 2.2 kt16:09 · avg 1.1 kt · gust 3.2 kt16:19 · avg 0.4 kt · gust 1.6 kt16:29 · avg 1.5 kt · gust 2.2 kt16:39 · avg 1.8 kt · gust 3.2 kt16:49 · avg 2.1 kt · gust 3.2 kt16:59 · avg 1.1 kt · gust 2.2 kt17:09 · avg 2.0 kt · gust 3.2 kt17:19 · avg 2.4 kt · gust 3.2 kt17:23 · avg 2.2 kt · gust 2.2 kt17:49 · avg 1.1 kt · gust 2.2 kt17:50 · avg 2.2 kt · gust 3.2 kt
avg wind gust ignition (8 kt) session (11 kt)
For Oct 14, 2026 · as written at the time

NO GO

100% daytime cloud + only 233 W/m² solar — no insolation to drive a thermal

🤖 ML — logistic experimental NO GO GO 31% · MAYBE 32% · NO GO 36%

Strongest inputs — (+) Bolzano pressure, dew-point spread; (−) morning solar.

🤖 ML — HGB · black box experimental NO GO GO 29% · MAYBE 17% · NO GO 54%

Most distinctive inputs: morning solar, Innsbruck pressure, daytime cloud.

Experimental shadow models — they never drive the verdict. How good are they? →

Previous forecast method

How the day was forecast at the time, before the rules were recalibrated — shown for comparison only.